Research on 3D Reconstruction Method of Transmission Line Towers based on Implicit Neural Representations

The high-precision 3D modeling of transmission lines can provide great convenience for daily operation and maintenance, staff training, and operation management. In response to the problems of low precision and rough surface of existing point cloud reconstruction models, this paper proposes a 3D reconstruction method for transmission line towers based on deep learning implicit neural representation. The tower tower feature information of the transmission line tower point cloud model is learned and extracted through the deep learning implicit representation method, and the point cloud model is refined on this basis to obtain a high-precision 3D reconstruction model. The experimental results show that the algorithm proposed in the paper has certain improvements in reconstruction effect and performance compared to Poisson reconstruction and RePCD-Net algorithm.